Recent advances in transportation geography demonstrate the ability to compute a metropolitan scale metric of social interaction opportunities based on the time-geographic concept of joint accessibility. The method we put forward in this article decomposes the social interaction potential (SIP) metric into interactions within and between social groups, such as people of different race, income level, and occupation. This provides a novel metric of exposure, one of the fundamental spatial dimensions of segregation. In particular, the SIP metric is disaggregated into measures of inter-group and intra-group exposure. While activity spaces have been used to measure exposure in the geographic literature, these approaches do not adequately represent the dynamic nature of the target populations. We make the next step by representing both the source and target population groups by space–time prisms, thus more accurately representing spatial and temporal dynamics and constraints. Additionally, decomposition of the SIP metric means that each of the group-wise components of the SIP metric can be represented at zones of residence, workplace, and specific origin–destination pairs. Consequently, the spatial variation in segregation can be explored and hotspots of segregation and integration potential can be identified. The proposed approach is demonstrated for synthetic cities with different population distributions and daily commute flow characteristics, as well as for a case study of the Detroit–Warren–Livonia MSA.

Thursday, November 5, 2015

A while ago, I've posted some of Bill Rankin's maps on segregation for different cities in the USA. Those maps got a lot public attention because they were innovative in the way they depicted racial segregation by representing each individual as one single dot and each ethnicity as a different color. Needless to say this approach gives a much better visual effect than traditional choropleth maps.

Inspired in Rankin's map, Nicolau de Gusmão (geography student from Sao Paulo) has created in a racial dot map of Rio. Pretty neat. He used data from the 2010 population census and he created the map using QGIS. His post is written in Portuguese, but you don't need to speak the language to appreciate the maps and get your own conclusion about segregation levels in Rio.